Highly active immunomodulatory therapy ameliorates accumulation of disability in moderately advanced and advanced multiple sclerosis
Bibliographic record
Abstract
OBJECTIVE: To evaluate variability and predictability of disability trajectories in moderately advanced and advanced multiple sclerosis (MS), and their modifiability with immunomodulatory therapy. METHODS: The epochs between Expanded Disability Status Scale (EDSS) steps 3-6, 4-6 and 6-6.5 were analysed. Patients with relapse-onset MS and having reached 6-month confirmed baseline EDSS step (3/4/6) were identified in MSBase, a global observational MS cohort study. We used multivariable survival models to examine the impact of disease-modifying therapy, clinical and demographic factors on progression to the outcome EDSS step (6/6.5). Sensitivity analyses with varying outcome definitions and inclusion criteria were conducted. RESULTS: For the EDSS 3-6, 4-6 and 6-6.5 epochs, 1560, 1504 and 1231 patients were identified, respectively. Disability trajectories showed large coefficients of variance prebaseline (0.92-1.11) and postbaseline (2.15-2.50), with no significant correlations. The probability of reaching the outcome step was not associated with prebaseline variables, but was increased by higher relapse rates during each epoch (HRs 1.58-3.07; p<0.001). A greater proportion of each epoch treated with higher efficacy therapies was associated with lower risk of reaching the outcome disability step (HRs 0.72-0.91 per 25%; p≤0.02). 3 sensitivity analyses confirmed these results. CONCLUSIONS: Disease progression during moderately advanced and advanced MS is highly variable and amnesic to prior disease activity. Lower relapse rates and greater time on higher efficacy immunomodulatory therapy after reaching EDSS steps 3, 4 and 6 are associated with a decreased risk of accumulating further disability. Highly effective immunomodulatory therapy ameliorates accumulation of disability in moderately advanced and advanced relapse-onset MS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".